Added WeightedSumFitness for retro-compatibility

Author: Tanguy Damart

bluepyopt/deapext/optimisations.py

@@ -25,6 +25,7 @@
 import random
 import logging
 import functools
+import numpy
 
 import deap
 import deap.base
@@ -44,6 +45,51 @@
 # settings of the algorithm can be stored in objects of these classes
 
 
+class WeightedSumFitness(deap.base.Fitness):
+
+    """Fitness that compares by weighted sum"""
+
+    def __init__(self, values=(), obj_size=None):
+        self.weights = [-1.0] * obj_size if obj_size is not None else [-1]
+
+        super(WeightedSumFitness, self).__init__(values)
+
+    @property
+    def weighted_sum(self):
+        """Weighted sum of wvalues"""
+        return sum(self.wvalues)
+
+    @property
+    def sum(self):
+        """Weighted sum of values"""
+        return sum(self.values)
+
+    def __le__(self, other):
+        return self.weighted_sum <= other.weighted_sum
+
+    def __lt__(self, other):
+        return self.weighted_sum < other.weighted_sum
+
+    def __deepcopy__(self, _):
+        """Override deepcopy"""
+
+        cls = self.__class__
+        result = cls.__new__(cls)
+        result.__dict__.update(self.__dict__)
+        return result
+
+
+class WSListIndividual(list):
+
+    """Individual consisting of list with weighted sum field"""
+
+    def __init__(self, *args, **kwargs):
+        """Constructor"""
+        self.fitness = WeightedSumFitness(obj_size=kwargs['obj_size'])
+        del kwargs['obj_size']
+        super(WSListIndividual, self).__init__(*args, **kwargs)
+
+
 class DEAPOptimisation(bluepyopt.optimisations.Optimisation):
 
     """DEAP Optimisation class"""
@@ -135,7 +181,7 @@ def setup_deap(self):
         self.toolbox.register(
             "Individual",
             deap.tools.initIterate,
-            functools.partial(utils.WSListIndividual, obj_size=OBJ_SIZE),
+            functools.partial(WSListIndividual, obj_size=OBJ_SIZE),
             self.toolbox.uniformparams)
 
         # Register the population format. It is a list of individuals